Total hip arthroplasty (THA) is an increasingly common procedure that replaces all or part of the hip joint. The average age of patients is decreasing, which in turn increases the need for more durable implants. Revisions in hip implants are frequently caused by three primary issues: femoral loading, poor fixation, and stress shielding. First, as the age of hip implant patients decreases, the hip implants are seeing increased loading, beyond what they were traditionally designed for. Second, traditional implants may have roughened surfaces but are not fully porous which would allow bone to grow in and through the implant. Third, traditional implants are too stiff, causing more load to be carried by the implant and shielding the bone from stress. Ultimately this stress shielding leads to bone resorption and implant loosening.

Additive manufacturing (AM) presents a unique opportunity for enhanced performance by allowing for personalized medicine and increased functionality through geometrically complex parts. Much research has been devoted to how AM can be used to improve surgical implants through lattice structures. To date, the authors have found no studies that have performed a complete 3D lattice structure optimization in patient specific anatomy. This paper discusses the general design of an AM hip implant that is personalized for patient specific anatomy and proposes a workflow for optimizing a lattice structure within the implant.

Using this design workflow, several lattice structured AM hip implants of various unit cell types are optimized. A solid hip implant is compared against the optimized hip implants. It appears the AM hip implant with a tetra lattice outperforms the other implant by reducing stiffness and allowing for greater bone ingrowth. Ultimately it was found that AM software still has many limitations associated with attempting complex optimizations with multiple materials in patient specific anatomy. Though software limitations prevented a full 3D optimization in patient specific anatomy, the challenges associated such an approach and limitations of the current software are discussed.

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